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The value of Radiomics combined with Machine Learning in the staging of liver Fibrosis

Fengxian Fan¹, Weiting Huang², Yanli Jiang¹, Wanjun Hu¹, Jing Zhang¹, and Jialiang Ren³
¹LanZhou University Second Hospital, LanZhou, China, ²LanZhou University, LanZhou, China, ³GE Healthcare, Shanghai, China

In this study, 244 people had liver pathologic and MRI were divided into training and testing cohorts to developed and validated radiomics models for differentiation of low(0-2) from high(3-4) stage fibrosis. The results showed radiomics models of T1WI had a powerful ability to stage fibrosis.

Figure 2. a. ROC curve analysis of radiomics models in the testing cohort (AUC=0.85). b. ROC curve analysis of Fibroscan(AUC=0.83), APRI(AUC=0.68), FIB-4(AUC=0.69).

Table 1.The eighteen valuable features.